Evaluation and comparison of MODIS and VIIRS aerosol optical depth (AOD) products over regions in the Eastern Mediterranean and the Black Sea. (1st January 2022)

• Record Type: Journal Article
• Authors: Ettehadi Osgouei, Paria; Roberts, Gareth; Kaya, Sinasi; Bilal, Muhammad; Dash, Jadunandan; Sertel, Elif
• Is Part Of: Atmospheric environment. Volume 268(2022)
• Publication Date: 2022-01-01
• Subjects: Aerosols -- MODIS -- VIIRS -- AERONET -- DB -- DT -- MAIAC -- Validation -- Inter-comparisons; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2021.118784
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Aerosol loading has direct and indirect impacts on radiative forcing and climate; additionally, exposure to high aerosol concentrations has adverse effects on human health. Several inversion algorithms are used to retrieve aerosol properties, primarily aerosol optical depth (AOD). Satellite aerosol products are available from several moderate spatial resolution sensors and provide information on the spatial and temporal dynamics of aerosol concentration. This study provides an evaluation and inter-comparison of multiple aerosol products from Terra and Aqua Moderate Resolution and Imaging Spectroradiometer (MODIS) and Suomi National Polar-Orbiting Partnership (Suomi NPP) Visible-Infrared Imager Radiometer Suite (VIIRS) between 2014 and 2018 in the Eastern Mediterranean and the Black Sea. This evaluation focuses on four MODIS aerosol products including Dark Target (DT) AOD retrievals at 10-km and 3-km spatial resolutions, Deep Blue (DB) AOD retrievals at10-km spatial resolution, Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD retrievals at 1-km spatial resolution, and VIIRS DB AOD retrievals at 6-km spatial resolution. Satellite-based AOD retrievals are validated against in-situ AOD measurements from three AERONET ground stations located in urban/land, rural/coastal, and ocean surfaces. The results show that Pearson's correlation coefficient (r) between the satellite AOD retrievals and AERONET AOD measurements range between 0.45 and 0.93 whilst the Root-Mean-Squared Errors (RMSE) varies from 0.047 to 0.159 which highlights the reliability of satellite AOD retrievals' in the region. The best performing products over the urban/land surface are the MODIS MAIAC and VIIRS DB aerosol products with the RMSE of 0.048–0.061 and a higher percentage (81%–89%) of retrievals falling within expected error for land. Over the ocean, the MODIS DT aerosol products have the lowest errors (RMSE 0.047–0.061) and the highest percentage (70%–80%) of retrievals falling within the expected error. The performances of all algorithms over the rural/coastal region are poorer in terms of over- and under-estimations of AOD with a small percentage of retrievals (48%–87%) within expected error. Among the satellite aerosol products, the VIIRS aerosol product performs better over the coastal area in terms of high correlation coefficient (r = 0.88), low error (RMSE = 0.059), and the large percentage of retrievals within expected error (88%). The poor performance found over the more complex coastal regions suggests further improvements are needed in land-water-sediment masks, surface reflectance estimation, and aerosol model assumptions over mixed surface types. The aerosol products show the highest agreement (r ∼ 0.77–0.98) over the ocean surface whilst the coastal site aerosol products verified the greatest dissimilarity in aerosol loading variations (r ∼ 0.50–0.91). Lastly, the good correlation (r > 0.73) between the VIIRS and MODIS AOD products illustrates the potential of VIIRS to provide aerosol data continuity with MODIS. Highlights: MODIS-MAIAC/VIIRS-DB AODs are best performing products over Eastern Mediterranean. Performance of DT, DB, MAIAC algorithms vary over different land surface types. The 3-km MODIS-DT AOD product is noisier than the 10-km AOD product over urban/land. All the retrieval algorithms show poor performance over the coastal site.